The AI takes a deep dive into the book "Systemic and Systematic Project Management" by J. Kasser (2019), exploring project management as a problem-solving paradigm that emphasizes the need for both systemic thinking, which considers the whole system, and systematic thinking, which involves a methodical, step-by-step approach. The book details various aspects of project lifecycle management, including planning methodologies like the "build a little test a little" method, cost and schedule estimation, and risk management strategies such as CRIP and ETL charts. It also addresses the human element in projects, discussing team staffing, motivation, communication, and ethical considerations. Throughout the text, complex project scenarios are broken down and explained using frameworks such as the System Development Process (SDP) and various levels of thinking, providing a comprehensive guide to successful project execution and problem resolution.
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Systems Engineering: A Paradigm Shift Analysis
The AI team takes a deep dive into research that began with the question, “Why do systems engineering textbooks cover such different material while claiming to represent the same discipline?”. The research investigates the evolution of systems engineering over seven decades, hypothesizing a paradigm shift rather than mere topical variation in literature. Utilizing AI-assisted analysis of textbooks from 1950 to 2023, the study identifies three evolutionary phases: an initial engineering science dominance, a subsequent transition period, and a current fragmentation characterized by the predominance of administrative approaches. The paper argues that this shift, from emphasizing analytical problem-solving to focusing on process coordination, has significant implications for education and practice, potentially explaining inconsistencies and challenges in the field. It also highlights how Model-Based Systems Engineering (MBSE) and INCOSE certifications may reinforce the administrative paradigm, calling for further systematic validation of these preliminary findings.
The preliminary analysis suggests a fundamental transformation in systems engineering. While the findings require validation through more rigorous research, they offer a framework for understanding disciplinary fragmentation. The paper advocates for "thoughtful integration that preserves the problem-solving capabilities necessary for breakthrough innovation as core professional competence, while maintaining the organizational coordination benefits of formal administrative process frameworks as supporting professional capabilities." This "systematic integration of both paradigms" is seen as the "greatest challenge and the greatest opportunity for the future of systems engineering education and practice."
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Applying Total Quality Management to systems engineering
The AI team take a deep dive into a 30-year old book, "Applying Total Quality Management to Systems Engineering," explores various facets of systems engineering within a Total Quality Management (TQM) framework. It details the Systems Development Life Cycle (SDLC), outlining phases from requirements definition and design to implementation, testing, and maintenance. The author emphasizes the importance of cost-effective engineering, process improvement, and risk mitigation, introducing concepts like anticipatory testing and metrics for product and process quality. Furthermore, the text examines contractual considerations, proposal development, and the critical role of effective communication and teamwork in achieving successful project outcomes, concluding with discussions on professional ethics and organizational improvement strategies.
Save money, the book is available from pre-owned or used book suppliers are very reasonable prices.
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The top 5 reasons why you can’t write good requirements
The AI team take a deep dive into a webinar in which Dr Joseph Kasser, outlines the top five reasons for difficulties in writing good requirements and proposes solutions. It highlights innovations in systems engineering, project management, and postgraduate education developed by the author. Kasser introduces unique learning programs utilizing the "Evercourse" lifelong learning format to address these challenges.
The webinar emphasizes practical knowledge and experience, offering affordable membership for professionals seeking to improve their skills. Ultimately, it serves as an invitation to learn more about overcoming common pitfalls in requirement writing through Kasser's methodologies.
Further information may be found at https://therightrequirement.com/educational-opportunities/how-to-write-good-requirements/
To find out how to join the course and its unique affordable cost, book a free call via the contact form at https://therightrequirement.com/the-right-requirement/contact/
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Hitchins’ Viable Systems Model
The AI team take a deep dive into Professor Hitchins concept of reference models for understanding systems, introducing his Generic Reference Model (GRM) from 1992, which encompasses form, function, and behavior. The text elaborates on these three aspects and then presents the Hitchins Viable Systems Model (H-VSM) as an evolution of the GRM's function model. The H-VSM is depicted as a layered model for analyzing open, autonomous, and viable systems, applicable to various entities from individuals to organizations. Practical application of the H-VSM through an Open/Operational Systems Engineering (OSE) approach is described, emphasizing mission and viability management. They also discuss how the H-VSM can be instantiated for dynamic simulations, such as a naval destroyer in combat, and even anthropomorphically. Ultimately, Hitchins presents a comprehensive framework for understanding and designing effective systems.
The AI team take a deep dive into successful innovative tools, practical and conceptual applications of systems thinking and beyond and systems engineering to various types of problems, summarizing the concepts behind the successes and usually drawing general conclusions for how the concepts may be used in other situations. The opinions expressed by the AI team in each deep dive are their own and have not been edited in any way.
While systems thinking provides an understanding of the problematic situation, you need to go beyond systems thinking to create solutions, especially innovative solutions.
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